3 papers
cs.LG2026
Deep Learning for Anomaly Detection in Railway Systems: A Structured Survey
Ammar Bouketta, Smail Niar, Hamza Ouarnoughi
Ensuring safe and reliable operation of modern railway systems increasingly relies on data-driven monitoring and intelligent fault detection. Deep learning has emerged as an effect…
cs.LG2026
Cycle-Aware Autoencoder with Cross-SignalConsistency for Railway Door Anomaly Detection
Ammar Bouketta, Smail Niar, Hamza Ouarnoughi +1
Passenger access doors are safety-critical subsystems in railway vehicles, yet detecting abnormal door behavior in real operation is challenging because faults are rare, diverse, a…
cs.NE2026
Hybrid Metaheuristic Combining the Dragonfly Algorithm and Tabu Search for the Traveling Salesman Problem
Ammar Bouketta
The Traveling Salesman Problem (TSP) is a classical NP-hard combinatorial optimization problem that aims to find the shortest Hamiltonian cycle visiting each city exactly once and…